


import warnings

from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor


lowerCAmelCase			=				logging.get_logger(__name__)


class 			_a				(     UpperCamelCase__     ):

							def __init__(				self:      Dict       ,		*UpperCamelCase_:      Optional[Any]       ,		**UpperCamelCase_:      Union[str, Any]				)     ->  None:





									"""simple docstring"""







									warnings.warn(
									    '''The class ImageGPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
									    ''' Please use ImageGPTImageProcessor instead.'''       ,		UpperCamelCase_       ,		)
									super().__init__(*UpperCamelCase_       ,		**UpperCamelCase_				)







def  lowerCAmelCase_	(lowerCAmelCase__:		int  ):





			"""simple docstring"""


			if num <= 0:
						raise ValueError("""Input must be a positive integer"""  )

			UpperCAmelCase_:		Tuple							      =     [True] * (num + 1)

			UpperCAmelCase_:		Tuple							      =     2
			while p * p <= num:
						if primes[p]:
									for i in range(p * p		,						num + 1		,						lowerCAmelCase__  ):
												UpperCAmelCase_:		Optional[Any]							      =     False
						p += 1

			return [prime for prime in range(2		,						num + 1  ) if primes[prime]]


if __name__ == "__main__":
	import doctest

	doctest.testmod()

	a      :  Optional[Any]			     =			int(input('Enter a positive integer: ').strip())
	print(prime_sieve_eratosthenes(user_num))






